Whenever you hear this term Machine Learning, what comes to your mind first?

Well, engineers, computer scientists, and IT people often use this term. It is not for only IT people but anyone who wants to learn and become a pro!

What is Machine Learning?

It is the scientific research and study of statistical models, algorithms that computer systems use to perform a specific task without any unambiguous instructions. Also, machine learning is a subpart of “Artificial Intelligence”. The design is done to enable work on the given data and make decisions, predictions without any manual instruction given to the program.

Usage – It is used in Email filtering, computer vision.

Difference between Artificial Intelligence and Machine Learning

ARTIFICIAL INTELLIGENCE

MACHINE LEARNING (ML)

AI – Artificial intelligence, where intelligence is called an achievement of knowledge and also have the ability to acquire knowledge.

ML refers to attaining knowledge or skill.

The technology aims to increase the chances of success and not accuracy.

The aim is to increase the accuracy, but it doesn’t focus on success.

It works as a smart computer.

It is a simple concept wherein the machine takes data from the user and learns from it.

AI is designed to be a decision-maker.

In the case of ML, it helps to learn new concepts from the data.

In this system it is designed to mimic humans, to respond in certain circumstances.

It includes creating self-learning algorithms.

AI finds the optimal solution.

ML will find the solution regardless it is optimal or not.

It is a system, hence it has many ways. let’s see the type of machine learning systems:

Supervised machine learning algorithms

Unsupervised machine learning algorithms

Semi-supervised machine learning algorithms

Reinforcement machine learning algorithms

Some facts: What exactly is Machine learning?

The IIT Bangalore and Upgrade aim to create the 11 months program to prepare professionals in the field of data science and machine learning.

The few objectives of the PG programs are to learn classification algorithms, create intelligent solutions like Chatbots, smart games, etc. Besides, you can participate in hackathons and develop a portfolio for industry projects.

Georgia Tech and edX offer an Online Master of Science in Analytics offering courses in Introduction to Analytics, Modeling, and Computing for Data Analytics, etc.

The University of Illinois offers online courses in Masters in Computer Science and Data Analytics.

So you see this field is closely related to AI, Data Mining and Data Analytics and emerging widely. Hence, you must research first for the same.

Previously these subjects were not of much importance but now they have good salary jobs in the industry.

Importance of Machine Learning

In this world of growing internet, has led us to the generation of the immense amount of data. Where will so much data go?

To process such a huge amount of data, machine learning is important. It can quickly develop models that can analyze bigger, complex data and deliver accurate results – even on a very huge scale.

Let the important tools required to create good machine systems:

Data preparation capabilities

Algorithms – basic and advanced

Scalability

Ensemble modeling

Automation and iterative processes

For some of you these terms would sound quite remote, well those who keep keen interest would understand the terms given above.

Use of Machine Learning

1. Financial Services

These companies use ML technology as a tool to get insights on data and prevent fraud. The insights give valuable information to the company related to decisions for trade and a lot more.

2. Government

The government uses this technology for public safety and detect frauds and avoid identity thefts.

3. Health care

In the case of health care, it is used to process patient’s data. This, in turn, helps the doctors to analyze data to identify trends that may lead to better diagnoses and treatment.

4. Retail

As we shop across various online websites, machine learning and data mining play a wide role in filtering the options for us. For example, if you’re viewing a product, a similar product shows up below under the recommended list. All these optimizations are the technology of machine learning.

5. Oil and gas

It is used to analyze the minerals in the ground. Additionally, the reorganization of oil distribution is done to make it more resourceful and cost-effective.

Now after discussing the fundamentals of Machine Learning, a question may arise in your mind. What can be the job profiles and salary for this stream?

This technology comes under the stream of Computer Science. Therefore, to qualify for this subject the candidate should thorough with basic computer science concepts, data structure, and algorithms.

If you take up Machine Learning (ML), you can be a/an

Engineer in this field

Senior ML Engineer

Lead ML Engineer

ML Engineer front office/back office

ML Software Engineer

Data Scientist

Senior Data Scientist

Senior Data Scientist IT

When you take up this course to study, it can bring many challenges in your path. Focus this course if you love to solve new problems and have a forte for technical stuff. Many times students take up this course and later realize this course was just not for them.

The average salary of an employee in this domain ranges from Rs. 60,000 to 1,00,000 monthly.

As this is a promising field, you may start from a small first. Learn more and move to large posts in the company to develop new technologies.